Electroencephalography (EEG) is a very popular, non-invasive method used in both medicine as well as research, to gain insight into how the human brain works. In most cases, this is a rather indirect method as we do not have access to the human brain while it functions. It is hence a complex task to tell where exactly the recorded activity comes from and identify which brain regions are its generators. To be able to make this connection, head models and different algorithms are being used to simulate the anatomy between the brain and the sensors (e.g. human tissue or bone).
We hypothesized that, the more individual information of an experimental subject we have available, the better the precision of the brain source identification should be. Such information can be obtained through anatomical MRI scans and precise knowledge of the sensor locations (i.e. the electrodes) during the experiments; yet these procedures oftentimes sum up to a significant time or financial cost. In our study we explored how these factors play a role in performing a better identification of the active brain sources. We focused on the hearing center of the brain, the primary auditory cortex (PAC). The PAC is a very small region on the temporal lobe of the brain, primarily responsible for relaying auditory information to other brain regions (see fig. 1). We additionally compared different algorithms, to investigate how dependent they are on the individual factors.
In sum, our findings demonstrate the benefit of using additional individualized information regarding brain anatomy and electrode positioning; they further support previous notions toward using a specific algorithm for investigating auditory processes. Such information can be crucial when selecting parameters for a study by considering existent constraints of the experiments; for example, incompatibilities between implants and MRI scanners. Our study can thereby help steer decisions towards experimental procedures and scientific resource allocation.
Our article appeared as a methods article in Frontiers of Neuroinformatics, in the special issue “From the Ear to The Brain”. In the spirit of accessible science, this open access journal hosts an impressive amount of literature on computational methods on neuroscience. Through the special issue focused on the auditory system, a collection of auditory-related topics offers an overview of new data analytics techniques for better understanding the human hearing.
Ignatiadis, Karolina; Barumerli, Roberto; Tóth, Brigitta; Baumgartner, Robert (2022): “Benefits of individualized brain anatomies and EEG electrode positions for auditory cortex localization”, in: Frontiers in Neuroinformatics for the special issue "From the Ear to the Brain".